1. Abstract For the performance measure approach (PMA) of RBDO, a transformation between the input random variables and the standard normal random variables is required to carry out the inverse reliability analysis. Since the transformation uses the joint cumulative density function (CDF) of input variables, the joint CDF should be known before carrying out RBDO. In many industrial RBDO problem...

Archimedean copulas are copulas determined by a specific real function, called the generator. Composited with the copula at a given point, this generator can be expressed as a linear form of generators of the considered point components. In this paper, we discuss the case where this function is expressed as a quadratic form (called here multivariate Archimatrix copulas). This allows extending A...

Abstract. Tail order of copulas can be used to describe the strength of dependence in the tails of a joint distribution. When the value of tail order is larger than the dimension, it may lead to tail negative dependence. First, we prove results on conditions that lead to tail negative dependence for Archimedean copulas. Using the conditions, we construct new parametric copula families that poss...

The authors extend to multivariate contexts the copula-based univariate time series modeling approach of Chen & Fan [X. Chen, Y. Fan, Estimation of copula-based semiparametric time series models, J. Econometrics 130 (2006) 307–335; X. Chen, Y. Fan, Estimation and model selection of semiparametric copula-based multivariate dynamic models under copula misspecification, J. Econometrics 135 (2006) ...

in this paper, we introduce a new kind of order, cesaro supermodular order, which includes supermodular order and stochastic order. for this new order, we show that it almost fulfils all desirable properties of a multivariate positive dependence order that have been proposed by joe (1997). also, we obtain some relations between it with other orders. finally, we consider different issues related...

This study aims to determine the copula-based model for estimating aggregate losses in traffic accident insurance. research method is descriptive quantitative. Determination of best and accuracy determined based on Akaike Information Criterion (AIC), smallest Root Mean Square Error (RMSE), Vuong Test. The results study, there a dependency relationship or correlation between frequency claims sev...

The mixture property of the general multivariate Pareto MP distributions has been studied by Yeh (2004a). Arnold (1996) mentioned that any mixing distribution with support (0,∞) is a candidate for a frailty model. This fact drives Yeh to study the frailty structure of the MP distributions. It is discerned that the MP distributions is in the one-parameter kvariate Clayton family with k-variate A...

To examine the asymmetry of financial data in detail, we have considered both the tail dependence with diverse copulas and Jung et al.’s [8] directional dependence by copula. From the empirical study in this paper, we have found that the tail dependence by Patton’s [11] modified symmetrized Joe-Clayton copula function did not show the asymmetry property sufficiently because there is no tail dep...

In this paper, we consider series-parallel and parallel-series systems with independent subsystems consisting of dependent homogeneous components whose joint lifetimes are modeled by an Archimedean copula. Then, by considering two such systems with different numbers of components within each subsystem, we establish hazard rate and reversed hazard rate orderings between the two system lifetimes,...

We introduce a statistical test for comparing the predictive accuracy of competing copula specifications in multivariate density forecasts, based on the Kullback-Leibler Information Criterion (KLIC). The test is valid under general conditions: in particular it allows for parameter estimation uncertainty and for the copulas to be nested or nonnested. Monte Carlo simulations demonstrate that the ...